Why Use Models and Simulations?
- EK 1.3.1E Computing enables creative exploration of both real and virtual phenomena.
- EU 2.3 Models and simulations use abstraction to generate new understanding and knowledge.
- EK 2.3.1A Models and simulations are simplified representations of more complex objects or phenomena.
- EK 2.3.1B Models may use different abstractions or levels of abstraction depending on the objects or phenomena being posed.
- EK 2.3.1C Models often omit unnecessary features of the objects or phenomena that are being modeled.
- EK 2.3.1D Simulations mimic real world events without the cost or danger of building and testing the phenomena in the real world.
- EK 2.3.2A Models and simulations facilitate the formulation and refinement of hypotheses related to the objects or phenomena under consideration.
- EK 2.3.2B Hypotheses are formulated to explain the objects or phenomena being modeled.
- EK 2.3.2C Hypotheses are refined by examining the insights that models and simulations provide into the objects or phenomena.
- EK 2.3.2D The results of simulations may generate new knowledge and new hypotheses related to the phenomena being modeled.
- EK 2.3.2E Simulations allow hypotheses to be tested without the constraints of the real world.
- EK 2.3.2F Simulations can facilitate extensive and rapid testing of models.
- EK 2.3.2G The time required for simulations is impacted by the level of detail and quality of the models, and the software and hardware used for the simulation.
- EK 2.3.2H Rapid and extensive testing allows models to be changed to accurately reflect the objects or phenomena being modeled.
In this lab, you will explore how models and simulations can be used to gain insight into real world phenomena.
On this page, you will learn why models and simulations are used instead of real world experiments.
A model is a computer representation of an object (or system of objects) in the real world. For example, you can have a model of an airplane or a highway.
A simulation is an algorithm that uses models to see what will happen over time under certain conditions. For example, if you model an airplane, you might simulate wind hitting it.
Models and simulations are computer representations of complex phenomena in the real world. They are used to explain or predict real life occurrences. There are many reasons to use computer simulations rather than real world experiments:
- Experimenting in the real world may be expensive. For example, a new design for an airplane might fall apart in strong winds. Using a computer to model the shape of the airplane and to simulate the wind behavior can eliminate some bad designs before building a real airplane.
- Experimenting in the real world may be time-consuming, such as testing the effects of a genetic mutation in a species across generations.
- Experimenting in the real world may be dangerous, such as testing whether a nuclear reactor will survive an earthquake.
- Experimenting in the real world may be unethical, such as giving a population a disease to test how fast it spreads.
Computer models rarely capture the full complexity of real situations. For example, models that scientists use to predict the impact of global climate change have to account for hundreds of interconnected factors such as wind patterns, the course of rivers, geological fault lines that cause earthquakes, and interactions of local plants and animals. It would be impossible to include all real interdependent factors in a model. So, researchers make simplifying assumptions in their models.
Researchers may use an iterative design process, starting with a very simple model and refining that model based on their past experiences to make it more realistic for the next simulation. Highly detailed models may push the limits of current computer speeds. So, researchers may have to limit the complexity of the model. Complex models and simulations depend on abstractions (simplifications) to avoid the many details of real world phenomena.
- As a class, come up with some examples of complex real life phenomena for which it would be impractical, impossible, dangerous, or unethical to conduct real world experiments.
- Explain how modeling and simulations may help with our understanding of these phenomena. What are some pros and cons of using computers to explore these situations?